Title
Initial assessment of neuro pressure gradients in carotid stenosis using 3D printed patient-specific phantoms.
Abstract
Purpose: Investigate the use of neuro pressure gradients (NPG) to assess the impact of carotid artery disease on distal flow conditions using 3D printed patient-specific phantoms. Materials and Methods: Seven patients (five various degrees of carotid artery disease, two healthy) underwent 320-detector row CT angiography (Aquilion ONE, Canon Medical Systems). The internal carotid, vertebral, basilar arteries, as well as the Circle of Willis, middle cerebral arteries (MCA), anterior cerebral arteries (ACA), and posterior cerebral arteries (PCA) were segmented using a Vitrea workstation (Vital Images). The patient anatomy was manipulated in Autodesk Meshmixer and each phantom was 3D printed using material that simulates the compliance of vasculature, Tango+, using a Stratasys Eden260V printer. Phantoms were connected in a pulsatile flow loop with physiological flow rates. Distal resistance was manipulated to simulate physiological conditions. The pressure was measured in the proximal internal carotid arteries and the distal right and left MCA to calculate the neuro pressure gradient (NPG). Results: All seven phantoms were successfully tested in the simulated physiological flow loop. Neuro pressure gradients (NPG) were measured in each phantom and demonstrated a dependence on percent stenosis and Circle of Willis anatomy. NPG ranged -0.67 to 1.10 mmHg/cm and moderately correlated with the stenosis grade and location, and the Circle of Willis configuration. Conclusions: We have successfully assessed the feasibility of measuring NPG in 3D printed patient-specific neurovasculature phantoms with carotid artery disease.
Year
DOI
Venue
2019
10.1117/12.2510279
Proceedings of SPIE
Keywords
Field
DocType
3D printed patient-specific phantoms,Neuro Pressure Gradient,3D printing,neurovasculature,blood flow simulations
Stenosis,Radiology,Pressure gradient,Medicine
Conference
Volume
ISSN
Citations 
10953
0277-786X
0
PageRank 
References 
Authors
0.34
0
6